1. 4-1 BUSI 240 Introduction to Information Systems Tuesday & Thursday 8:05am – 9:30am Wyant Lecture Hall Please sign the roster on the back table.

2. 5-2 AOL’s Bet on Another Makeover AOLAOL is trying to remake itself, yet again. The new strategy in many ways resembles the old strategy: make acquisitions to attract traffic and reverse a continuing decline in advertising and revenue from its dial-up Internet service. In the latest iteration of its do-over, it is paying $315 million to buy the liberal news commentary site The Huffington Post, not long after paying $25 million to buy TechCrunch, the Silicon Valley technology news blog.Huffington Post http://www.nytimes.com/2011/02/08/technology/08aol.html?_r=2&ref=technology Current Events – What’s going on?

3. 5-3 Verizon Has Already Sold 500,000 iPhones Estimates place the number of iPhone 4s sold by Verizon Wireless during its short-lived pre-sale at more than half a million. function showDesc(img) { var element = document.getElementById("videoBoxDisplayAreaText"); if(element) element.innerHTML = img.alt; }; JPMorgan analyst Phil Cusick said in a note to clients today that it's likely 500,000 people purchased an iPhone 4 from Verizon Wireless during the 17-hour-long pre-sale that took place on February 3.note to clients In order to reach this estimate, Cusick looked back at some clues given by Verizon Wireless in the past. http://www.informationweek.com/blog/main/archives/2011/02/verizon_has_alr.html Current Events – What’s going on?

4. 5-4 Quiz #2 Should have been taken by now.

5. 4-5 Assignment #2 Select a product to evaluate: Digital camera Cell phone MP3 player Car Computer Follow the steps on the spreadsheet to evaluate three models of the product Due February 22 nd Submit assignment to eComanion’s Drop Box

6. 5-6 Assignment #2 Web sites with product reviews: www.cnet.com www.consumerreports.org www.consumersearch.com www.epinions.com review.zdnet.com www.consumerreview.com

7. Data Resource Management Data Concepts Database Management Types of Databases Chapter 5a5a McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

8. 5-8 Examples of logical data elements

9. 5-9 Fundamental Data Concepts Character: single alphabetic, numeric or other symbol Field or data item: a grouping of related characters Represents an attribute (a characteristic or quality) of some entity (object, person, place or event) Example: salary Record: grouping of all the fields used to describe the attributes of an entity Example: payroll record with name, SSN and rate of pay

10. 5-10 Fundamental Data Concepts File or table: a group of related records Database: an integrated collection of logically related data elements

11. 5-11 Electric Utility Database Source: Adapted from Michael V. Mannino, Database Application Development and Design (Burr Ridge, IL: McGraw-Hill/Irwin, 2001), p. 6.

12. 5-12 Database Structures Hierarchical Network Relational Object-oriented Multidimensional

13. 5-13 Hierarchical Structure Early DBMS structure Records arranged in tree-like structure Relationships are one-to-many

14. 5-14 Hierarchical Structure

15. 5-15 Network Structure Used in some mainframe DBMS packages Many-to-many relationships

16. 5-16 Network Structure

17. 5-17 Relational Structure Most widely used structure Data elements are viewed as being stored in tables Row represents record Column represents field Can relate data in one file with data in another file if both files share a common data element Provide more flexibility than hierarchical databases because they allow users to easily receive information in response to ad hoc queries.

18. 5-18 Relational Structure

19. 5-19 Relational Operations Select: Create a subset of records that meet a stated criterion Example, select employees who make more than $30,000 Join Combine two or more tables temporarily Looks like one big table Project Create a subset of columns in a table

20. 5-20 Multidimensional Structure Variation of relational model Uses multidimensional structures to organize data Data elements are viewed as being in cubes Popular for analytical databases that support Online Analytical Processing (OLAP)

21. 5-21 Multidimensional Model

22. 5-22 Object-oriented Structure Object consists of Data values describing the attributes of an entity Operations that can be performed on the data Encapsulation: Combine data and operations Inheritance: New objects can be created by replicated some or all of the characteristics of parent objects

23. 5-23 Object-oriented Structure Source: Adapted from Ivar Jacobsen, Maria Ericsson, and Ageneta Jacobsen, The Object Advantage: Business Process Reengineering with Object Technology (New York: ACM Press, 1995), p. 65. Copyright @ 1995, Association for Computing Machinery. By permission.

24. 5-24 Object-oriented Structure Used in Object-oriented database management systems (OODBMS) Supports complex data types Examples, graphic images, video clips, web pages

25. 5-25 Evaluation of Database Structures Hierarchical Worked for structured routine transaction processing Can’t handle many-to-many relationships Network More flexible than hierarchical Unable to handle ad hoc requests Relational Easily respond to ad hoc requests Easier to work with and maintain Not as efficient or quick as hierarchical or network

26. 5-26 Database Development Database Administrator (DBA) In charge of enterprise database development Data Definition Language (DDL) Develop and specify the data contents, relationships and structure These specifications are stored in data dictionary Data dictionary Data base catalog containing metadata Metadata – data about data

27. 5-27 Database Development

28. 5-28 Data Planning Process Enterprise Model Defines basic business process of the enterprise Defined by DBAs and designers with end users Data Modeling Relationships between data elements Entity Relationship Diagram (ERD) common tool for modeling

29. 5-29 Entity Relationship Diagram

30. 5-30 Database Design Process Logical design Schema – overall logical view of relationships Subschema – logical view for specific end users Data models for DBMS Physical design How data are to be stored and accessed on storage devices

31. 5-31 Logical and Physical Database Views